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4 courses found
Computer Science
IDDept.Crs.Sect.TitleCr.DaysTimeDatesLocationInstructorMethodSize
265825CS232215 4M W F9:00am - 9:50am1.12.26-5.7.26HSH 213Neville, FrancoisHYFL0/14
H12:00pm - 1:50pm1.12.26-5.7.26S 371Neville, FrancoisHYFL
Course instruction is delivered both in-person (section 15) and online asynchronous (section 85). Choose the section that is your primary participation method. As a multimodal offering, students have the option to participate in either section on any day.
Topics include recursion and the study of object-oriented concepts including encapsulation, inheritance and polymorphism. It includes the study of fundamental data structures including strings, lists, stacks, queues, containers classes, binary trees, and hash tables. Also includes a group-oriented software design and implementation project. Includes a two-hour lab. Prerequisite: CS 2321.
265826CS232285 41.12.26-5.7.26Neville, FrancoisONL1/14
1.12.26-5.7.26Neville, FrancoisHYFL
Course instruction is delivered both in-person (section 15) and online asynchronous (section 85). Choose the section that is your primary participation method. As a multimodal offering, students have the option to participate in either section on any day.
Topics include recursion and the study of object-oriented concepts including encapsulation, inheritance and polymorphism. It includes the study of fundamental data structures including strings, lists, stacks, queues, containers classes, binary trees, and hash tables. Also includes a group-oriented software design and implementation project. Includes a two-hour lab. Prerequisite: CS 2321.
265828CS335001 3T H9:30am - 10:45am1.12.26-5.7.26HSH 115Neville, Francois 0/35
Uses a language suitable for creating event-driven programs while focusing on methodology suitable for developing event handlers in windows-oriented programs. Prerequisite: CS 2322 or equivalent.
265827CS375201 3M W F11:00am - 11:50am1.12.26-5.7.26HSH 205Neville, Francois 0/35
This course will provide an investigation into common Data Mining models, methods and techniques pioneered within the field of Artificial Intelligence. Topics covered may include any/all of the following: knowledge representation, clustering schema, decision trees and neural networks. Some student facility with mathematics and basic statistics is assumed. Prerequisites: CS 3528. May not be offered every year.

Delivery Method Key

  • No delivery method shown indicates course is delivered in-person on-campus.
  • BLND Blended/hybrid: 25-75% of course is delivered online with regularly scheduled in-person meetings.
  • HYFL Course instruction is delivered both in-person and online, you choose the method that is right for you.
  • ONL Course is delivered completely online.
  • ONLP Course is delivered completely online with proctored exams or up to two in-person meetings.
  • ONLS Course is delivered completely online with all or some synchronous class meetings.

Course data last update: 2025-10-28 5:15:56am
Next course data update: 2025-10-28 5:45:42am